【python】去除水印的几种方式_业界新闻

发布时间:2024-07-13 20:29

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1、python调用FFMEPG的delogo函数去除水印

要使用Python调用FFmpeg的delogo filter去除视频水印，你需要使用subprocess模块运行FFmpeg命令。以下是一个简单的Python脚本示例：

import subprocess   def remove_watermark(input_video, output_video, logo_x, logo_y, logo_width, logo_height):     # 构建FFmpeg命令     command = [         'ffmpeg',         '-i', input_video,         '-vf', f'delogo=x={logo_x}:y={logo_y}:w={logo_width}:h={logo_height}',         output_video     ]          # 运行FFmpeg命令     subprocess.run(command)   # 使用函数去除水印 remove_watermark('input.mp4', 'output.mp4', 10, 10, 100, 100)

使用说明视频：https://www.bilibili.com/video/BV1Jg4y1e7JJ/?spm_id_from=pageDriver

2、使用opencv-python库来处理视频帧

要在Python中去除视频水印，可以使用opencv-python库来处理视频帧，并结合图像处理技术，如图像修复或者图层混合。以下是一个简单的示例，演示如何使用OpenCV去除静态图像水印：

import cv2 import numpy as np   def remove_watermark(video_path, watermark_path, output_path):     # 读取视频和水印图像     cap = cv2.VideoCapture(video_path)     watermark = cv2.imread(watermark_path, cv2.IMREAD_UNCHANGED)     watermark = cv2.cvtColor(watermark, cv2.COLOR_BGR2GRAY)     watermark = cv2.GaussianBlur(watermark, (5, 5), 0)       # 获取水印的mask     _, mask = cv2.threshold(watermark, 1, 255, cv2.THRESH_BINARY_INV)       while True:         ret, frame = cap.read()         if not ret:             break           # 将水印区域替换为视频帧的背景         frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)         seamless_clone = cv2.seamlessClone(watermark, frame, mask, center, cv2.NORMAL_CLONE)           # 写入去水印后的视频帧         output_video.write(seamless_clone)       cap.release()     output_video.release()   # 使用函数去除视频中的水印 remove_watermark('input_video.mp4', 'watermark.png', 'output_video.mp4')

请注意，这个示例使用了seamlessClone函数，它要求水印区域的中心与背景相匹配，并且假设水印背景是纯色或者与视频背景融合得当。如果这些条件不满足，可能需要更复杂的图像处理技术，例如图像修复或深度学习去水印方法。

示例2
下面是使用OpenCV去除水印的Python代码示例：

import cv2 import numpy as np   # 读取视频和水印图像 video_path = 'video_with_watermark.mp4' watermark_path = 'watermark.png' cap = cv2.VideoCapture(video_path)   # 读取视频的宽、高和帧数 frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)) frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) fps = cap.get(cv2.CAP_PROP_FPS)   # 读取水印图像 watermark = cv2.imread(watermark_path, cv2.IMREAD_UNCHANGED) watermark_gray = cv2.cvtColor(watermark, cv2.COLOR_BGR2GRAY)   # 创建输出视频 out = cv2.VideoWriter('video_without_watermark.mp4', cv2.VideoWriter_fourcc(*'XVID'), fps, (frame_width, frame_height))   while(cap.isOpened()):     ret, frame = cap.read()     if ret:         # 转换为灰度图像         gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)                  # 使用cv2.matchTemplate()寻找水印的位置         res = cv2.matchTemplate(gray_frame, watermark_gray, cv2.TM_CCOEFF_NORMED)         min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)                  # 计算水印的位置         top_left = max_loc         bottom_right = (top_left[0] + watermark_gray.shape[1], top_left[1] + watermark_gray.shape[0])                  # 绘制矩形框覆盖水印         cv2.rectangle(frame, top_left, bottom_right, (0, 0, 0), thickness=watermark_gray.shape[0])                  # 写入去水印后的帧         out.write(frame)                  cv2.imshow('Video', frame)         if cv2.waitKey(1) & 0xFF == ord('q'):             break     else:         break   cap.release() out.release() cv2.destroyAllWindows()

3、python实战之去除视频水印&字幕，完整代码

import os import sys import cv2 import numpy from moviepy import editor   VIDEO_PATH = 'video' OUTPUT_PATH = 'output' TEMP_VIDEO = 'temp.mp4'     class WatermarkRemover():       def __init__(self, threshold: int, kernel_size: int):         self.threshold = threshold  # 阈值分割所用阈值         self.kernel_size = kernel_size  # 膨胀运算核尺寸         #根据用户手动选择的ROI（Region of Interest，感兴趣区域）框选水印或字幕位置。     def select_roi(self, img: numpy.ndarray, hint: str) -> list:         '''     框选水印或字幕位置，SPACE或ENTER键退出     :param img: 显示图片     :return: 框选区域坐标     '''         COFF = 0.7         w, h = int(COFF * img.shape[1]), int(COFF * img.shape[0])         resize_img = cv2.resize(img, (w, h))         roi = cv2.selectROI(hint, resize_img, False, False)         cv2.destroyAllWindows()         watermark_roi = [int(roi[0] / COFF), int(roi[1] / COFF), int(roi[2] / COFF), int(roi[3] / COFF)]         return watermark_roi         #对输入的蒙版进行膨胀运算，扩大蒙版的范围     def dilate_mask(self, mask: numpy.ndarray) -> numpy.ndarray:           '''     对蒙版进行膨胀运算     :param mask: 蒙版图片     :return: 膨胀处理后蒙版     '''         kernel = numpy.ones((self.kernel_size, self.kernel_size), numpy.uint8)         mask = cv2.dilate(mask, kernel)         return mask          #根据手动选择的ROI区域，在单帧图像中生成水印或字幕的蒙版。     def generate_single_mask(self, img: numpy.ndarray, roi: list, threshold: int) -> numpy.ndarray:         '''     通过手动选择的ROI区域生成单帧图像的水印蒙版     :param img: 单帧图像     :param roi: 手动选择区域坐标     :param threshold: 二值化阈值     :return: 水印蒙版     '''         # 区域无效，程序退出         if len(roi) != 4:             print('NULL ROI!')             sys.exit()           # 复制单帧灰度图像ROI内像素点         roi_img = numpy.zeros((img.shape[0], img.shape[1]), numpy.uint8)         start_x, end_x = int(roi[1]), int(roi[1] + roi[3])         start_y, end_y = int(roi[0]), int(roi[0] + roi[2])         gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)         roi_img[start_x:end_x, start_y:end_y] = gray[start_x:end_x, start_y:end_y]           # 阈值分割         _, mask = cv2.threshold(roi_img, threshold, 255, cv2.THRESH_BINARY)         return mask       #通过截取视频中多帧图像生成多张水印蒙版，并通过逻辑与计算生成最终的水印蒙版     def generate_watermark_mask(self, video_path: str) -> numpy.ndarray:         '''     截取视频中多帧图像生成多张水印蒙版，通过逻辑与计算生成最终水印蒙版     :param video_path: 视频文件路径     :return: 水印蒙版     '''         video = cv2.VideoCapture(video_path)         success, frame = video.read()         roi = self.select_roi(frame, 'select watermark ROI')         mask = numpy.ones((frame.shape[0], frame.shape[1]), numpy.uint8)         mask.fill(255)           step = video.get(cv2.CAP_PROP_FRAME_COUNT) // 5         index = 0         while success:             if index % step == 0:                 mask = cv2.bitwise_and(mask, self.generate_single_mask(frame, roi, self.threshold))             success, frame = video.read()             index += 1         video.release()           return self.dilate_mask(mask)       #根据手动选择的ROI区域，在单帧图像中生成字幕的蒙版。     def generate_subtitle_mask(self, frame: numpy.ndarray, roi: list) -> numpy.ndarray:         '''     通过手动选择ROI区域生成单帧图像字幕蒙版     :param frame: 单帧图像     :param roi: 手动选择区域坐标     :return: 字幕蒙版     '''         mask = self.generate_single_mask(frame, [0, roi[1], frame.shape[1], roi[3]], self.threshold)  # 仅使用ROI横坐标区域         return self.dilate_mask(mask)       def inpaint_image(self, img: numpy.ndarray, mask: numpy.ndarray) -> numpy.ndarray:         '''     修复图像     :param img: 单帧图像     :parma mask: 蒙版     :return: 修复后图像     '''         telea = cv2.inpaint(img, mask, 1, cv2.INPAINT_TELEA)         return telea         def merge_audio(self, input_path: str, output_path: str, temp_path: str):         '''     合并音频与处理后视频     :param input_path: 原视频文件路径     :param output_path: 封装音视频后文件路径     :param temp_path: 无声视频文件路径     '''         with editor.VideoFileClip(input_path) as video:             audio = video.audio             with editor.VideoFileClip(temp_path) as opencv_video:                 clip = opencv_video.set_audio(audio)                 clip.to_videofile(output_path)       def remove_video_watermark(self):         '''     去除视频水印     '''         if not os.path.exists(OUTPUT_PATH):             os.makedirs(OUTPUT_PATH)           filenames = [os.path.join(VIDEO_PATH, i) for i in os.listdir(VIDEO_PATH)]         mask = None           for i, name in enumerate(filenames):             if i == 0:                 # 生成水印蒙版                 mask = self.generate_watermark_mask(name)               # 创建待写入文件对象             video = cv2.VideoCapture(name)             fps = video.get(cv2.CAP_PROP_FPS)             size = (int(video.get(cv2.CAP_PROP_FRAME_WIDTH)), int(video.get(cv2.CAP_PROP_FRAME_HEIGHT)))             video_writer = cv2.VideoWriter(TEMP_VIDEO, cv2.VideoWriter_fourcc(*'mp4v'), fps, size)               # 逐帧处理图像             success, frame = video.read()               while success:                 frame = self.inpaint_image(frame, mask)                 video_writer.write(frame)                 success, frame = video.read()               video.release()             video_writer.release()               # 封装视频             (_, filename) = os.path.split(name)             output_path = os.path.join(OUTPUT_PATH, filename.split('.')[0] + '_no_watermark.mp4')  # 输出文件路径             self.merge_audio(name, output_path, TEMP_VIDEO)       if os.path.exists(TEMP_VIDEO):         os.remove(TEMP_VIDEO)       def remove_video_subtitle(self):         '''     去除视频字幕     '''         if not os.path.exists(OUTPUT_PATH):             os.makedirs(OUTPUT_PATH)           filenames = [os.path.join(VIDEO_PATH, i) for i in os.listdir(VIDEO_PATH)]         roi = []           for i, name in enumerate(filenames):             # 创建待写入文件对象             video = cv2.VideoCapture(name)             fps = video.get(cv2.CAP_PROP_FPS)             size = (int(video.get(cv2.CAP_PROP_FRAME_WIDTH)), int(video.get(cv2.CAP_PROP_FRAME_HEIGHT)))             video_writer = cv2.VideoWriter(TEMP_VIDEO, cv2.VideoWriter_fourcc(*'mp4v'), fps, size)               # 逐帧处理图像             success, frame = video.read()             if i == 0:                 roi = self.select_roi(frame, 'select subtitle ROI')               while success:                 mask = self.generate_subtitle_mask(frame, roi)                 frame = self.inpaint_image(frame, mask)                 video_writer.write(frame)                 success, frame = video.read()               video.release()             video_writer.release()               # 封装视频             (_, filename) = os.path.split(name)             output_path = os.path.join(OUTPUT_PATH, filename.split('.')[0] + '_no_sub.mp4')  # 输出文件路径             self.merge_audio(name, output_path, TEMP_VIDEO)           if os.path.exists(TEMP_VIDEO):             os.remove(TEMP_VIDEO)     if __name__ == '__main__':     sel=input('1：去水印, 2:去字幕\n')     if sel=='1':         remover = WatermarkRemover(threshold=80, kernel_size=5)         remover.remove_video_watermark()     if sel=='2':         remover = WatermarkRemover(threshold=80, kernel_size=5)         remover.remove_video_subtitle()